Fox

Do you think we can do this dynamically with AngularJS rather than with data points? One advantage doing it dynamically is we can change the bin group dynamically. What do you think?

BR,
Ricardo

var prevState = state.lastValue(1);print(prevState)
if(state.value && !prevState.value)
{
   timeTracker.set(0);
   LOG.info("timestracker set")
   
}

else if(prevState.value && !state.value)
{
    var prevTimestamp = timeTracker.time;
    var newTimestamp = state.time;
    
    var timespent = (newTimestamp - prevTimestamp)/60000.0; //In minutes
    timeTracker.set(timespent,newTimestamp);
   LOG.info("time spent")
   LOG.info(timespent)
   
    if(timespent<1)
    {
        
        //LOG.info("less than one")
        lessThanOne.set(timespent);
    }
    else if(timespent>=1 && timespent<10)
    {
        //LOG.info("less than ten")
        lessThanTen.set(timespent,newTimestamp);
    }
    else if(timespent>=10)
    {
        //LOG.info("more than ten")
        moreThanTen.set(timespent,newTimestamp);
    }
}

Fox

The occupancy data point's logging type is set to "When point value changes".

BR,
Ricardo

Fox

Thank you for your follow up. I don't understand which initial suggestion you are referring to, but I have further explored with the idea of using a meta data point for occupiedTime in sec.

The following is the script for the meta data point and it is executed when the occupancy binary (0) is updated (update context checked).

// return o.past(HOUR, 1).get(true).runtime / (60*1000)

curState = o.value;
lastState = o.lastValue(false).value;

if(curState == false) { //falling edge only
    if(lastState != false) {
        duration = (o.time - o.lastValue(false).time) / 1000;
        LOG.info(o.time);
        LOG.info(o.lastValue(false).time);
        return duration;
}

However, this implementation has a glitch that it generates "zero" when occupancy data points goes from "false" to "true" (e.g. rising edge).

With this occupiedTime meta data point, I can now generate bar charts showing the total occupied time by hour and possible manipulating the pointValues to generate a new series in percent. Next I will have to figure out how to do histogram (binning) the different occupied time.

BR,
Ricardo

Would you suggest to change the meta data point from update hourly interval to possibly update by context update?

No because that means your code would fire and look at the previous hour every time an update came in.

However, the client would like to do further analytics by binning the occupied time into 3 groups: <1 min, <10min and >10min.

Then I advise you look at my initial suggestion as I figured this would happen. You need this to work as occupied events, not just overall statistics. These events can then be evaluated and set a value on a datapoint that represents each timeframe. I'd advise a scripting datasource in this instance as each datapoint mentioned all relates basck to the same script.

Also, please read the docs and give things a go. We're not here to do your job for you.

The StartsAndRuntimeList object is returned by Binary and Multistate points. It contains the following properties:

periodStartTime (integer) the start time used for the calculation
periodEndTime (integer) the end time used for the calculation
--> count (integer) count of the total number of entries  
startValue: the value before or exactly at the period start time
firstValue: the first value in the period
firstTime: (integer) the time of the first value
lastValue: the last value in the period
lastTime: (integer) the time of the last value
data: (array) the list of individual StartAndRuntime objects.
Each StartAndRuntime object has the following properties:

value: (boolean for Binary, integer for Multistate) the point state to which the remaining properties apply 
starts: (integer) the number of times the state was entered over the period
--> runtime: (integer) the amount of time in milliseconds the point was in the state over the period
proportion: (float) the proportion of the period the point was in the state (runtime / real duration)

Fox

Also any suggestions on how to create a pie chart to present the distribution of the three binned groups?

BR,
Ricardo

Edit and thank you Fox!

Fox

return b.past(HOUR, 1).get(true).percentage;

Check the docs:

http://docs-v4.mango-os.com/about-mango-java-script

1. use a meta point to have start (0) and stop (finished time in minutes) then sum the results up into an hourly period with another meta point to derive hourly percentages.

2. do the above with a dedicated component to the same thing with a single pull of all values in a given time frame and calculate it all in one go.

3. possibly use ma statistics to derive mean and average values/times. I do not use this directive as it has no application for me at this time and is a bit resource intensive.

Good luck

Fox